Post on 27-Dec-2015
Lydia B. Zablotska, MD, PhDAssociate ProfessorDepartment of Epidemiology and Biostatistics
With thanks to Erin Richman, ScD
Design features of cohort and case-control studies
Week 2 - Cohort and C-C Studies1
Highlights from Last Week
I. Theories of causal inference: i. Inductiveii. Deductiveiii. Other (refutationist, bayesian)
II. Causal models (heuristics): i. Rothman’s sufficient-component cause model (‘causal pies’)ii. Greenland and Morgenstern’s counterfactual model (‘potential
outcomes’)iii. Graphical models (DAGs)
III. Practice of causal inference:I. A. Bradford Hills causal guidelines (with caveats)II. Surgeon General’s causal criteria
Week 2 - Cohort and C-C Studies2
Highlights from Last Week
Sufficient-component cause model Useful for examining multiple risk factors (‘web of causation’), but omits
discussion of origins of causes, focuses on proximal causes, and ignores induction period
Does not address indirect effects Causes of disease in individuals or groups of individuals, not in populations Does not consider factors that control distribution of risk factors Ignores dynamic non-linear relations
Counterfactual model Can be applied at individual or population level Specifies what would happen to individuals or populations under alternative
patterns of exposure Forces researchers to think about operational definitions of cases and
controls, sampling schemes, and other important design questions One of the two conditions in the definitions of the effect measures must be
contrary to fact – exposures or treatment vs. a reference conditionWeek 2 - Cohort and C-C Studies3
Learning Objectives
Classification of epidemiologic studies Cohort Studies
– Closed vs. open cohorts– Classifying person-time– Lag time
Case-control Studies– Selection of cases and controls– Measures of association– Control sampling schemes– Sources of controls
Field methods, i.e. nuts and bolds of conducting observational studies
Week 2 - Cohort and C-C Studies4
Classifications by:
• Approach to data collection
• Goal
• Timing and directionality
• Unit of analysis
Epidemiological Methods
Week 2 - Cohort and C-C Studies5
• Experimental
–RCTs, field trials, community intervention
and cluster randomized trials
• Quasi-experimental
–natural disaster studies
• Non-experimental or observational
–cohort, case-control, ecological
Classification by approach to data collection
Week 2 - Cohort and C-C Studies6
• Descriptive
– ecological correlational studies, case reports,
case series, cross-sectional surveys
• Analytic
– observational studies and intervention studies
(RCTs)
Classification by goal
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– Directionality: "Which did you observe first, the exposure or the disease?“
– forward (RCT, cohort) – backwards (case-control)
– Timing: “Has the information being studied already occurred before the study actually began?"
– retrospective and prospective cohort studies
Classification by timing and directionality
Week 2 - Cohort and C-C Studies8
Classification by timing and directionality
Retrospective cohort study
past present future
x
RCT
exposed
unexposed
Diseased
Non-diseased
Diseased
Non-diseased
exposed
unexposed
Diseased
Non-diseased
Diseased
Non-diseased
9
– What is a unit?
Observations for which outcome and exposure are
measured
– Individual-level variables are properties of individuals
– ecological variables are properties of groups,
organizations or places
Classification by unit of analysis
Week 2 - Cohort and C-C Studies10
Experimental study Cohort study Case‑control study
Each design represents a different way of harvesting information.
Selection of one over another depends on the particular research question, concerns of about data quality and efficiency, and practical and ethical considerations .
Main Epidemiologic Study Designs for Testing Hypotheses
Week 2 - Cohort and C-C Studies11
Main Epidemiologic Study Designs for Testing Hypotheses, cont.
Randomized controlled trial = Investigator assigns exposure and follows participants overtime to ascertain the outcome
Cohort study = Analogous to RCT, but investigator does not assign exposure
Case-control study = Analogous to cohort study, but with more efficient sampling
Week 2 - Cohort and C-C Studies12
Cohort Studies
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1. Randomization of treatment so groups are comparable on known and unknown confounders.
2. Use placebo in order to reduce bias.
3. Blinding to avoid bias in outcome ascertainment.
Principles of experimental studies
Week 2 - Cohort and C-C Studies14
1. Randomization of treatment so groups are comparable on known and unknown confounders.
Can't randomize in an observational study so select a comparison group as alike as possible to the exposed group
Principles of experimental studies applied to observational cohort studies
Week 2 - Cohort and C-C Studies15
2. Use placebo in order to reduce bias.
Can’t use placebo in observational studies so you must make the groups as comparable as possible.
Principles of experimental studies applied to observational cohort studies
Week 2 - Cohort and C-C Studies16
3. Blinding to avoid bias in outcome ascertainment.
In a cohort study, it is crucial to have high follow-up rates and comparable ascertainment of outcomes in the exposed and comparison groups.
You can blind the investigators conducting follow up and confirming the outcomes.
Principles of experimental studies applied to observational cohort studies
Week 2 - Cohort and C-C Studies17
General definition of Cohort Studies
Investigator identifies a group of individuals who are free of the disease, but at risk for the disease
Classifies individuals into 2+ groups based on exposure
Follows over time to determine who develops disease
Week 2 - Cohort and C-C Studies18
Closed Cohorts
Fixed population– After start of follow-up, no one can be added– Closely resemble RCT as follow-up starts at randomization
Membership-defining event– Cohort of persons born in 2012 (calendar time)– Cohort formed at entry into UCSF medical school (an event)
Can directly calculate:– Risk ratio– Incidence rate ratio– Odds ratio
Week 2 - Cohort and C-C Studies19
Closed Cohorts, cont.
Limitations of incidence proportion (cumulative incidence) analyses:
– Loss to follow-up– Competing risks– For certain outcomes (e.g. death), incidence proportion
tends toward 1 over time– Exposures may change over time
Solution: Calculate Incidence Rates
Week 2 - Cohort and C-C Studies20
Open Cohorts (Dynamic Cohorts)
No fixed roster – person-time accrued from a potentially changing roster of individuals
– Residents of California– Members of Kaiser Permanente
Individuals can contribute varying amounts of person-time
Individuals can leave and re-enter the cohort– Connecticut Tumor Registry
Individuals can contribute person-time to multiple exposure categories over time
– Occupationally exposed workers
Week 2 - Cohort and C-C Studies21
Open Cohorts, cont.
Rates can be directly measured Incidence proportion cannot be directly measured Can calculate IP from IR assuming:
– The IR is constant over the follow-up periods (j)– No competing risks or loss to follow-up related to disease risk– Number of events in each time interval is small relative to
number of people at risk in that time interval
Use for communicability of results
Incidence Proportion = jj tIRe1
Week 2 - Cohort and C-C Studies22
Classifying Person-Time
Each unit of person-time contributed by an individual has its own exposure classification
Must consider the etiologically relevant exposure Exposure may change over time
Exposure Disease Initiation
Disease Detection
Induction period Latent period
Week 2 - Cohort and C-C Studies23
Classifying Person-Time, cont.
Time at which exposure occurs ≠ time at risk of exposure effects
– Radiation from an atomic bomb and risk of cancer
Only the time at risk for exposure effects should be counted in the denominator of the incidence rate for that level of exposure
If the induction time is not known, can estimate empirically by calculating the incidence rates for differing categories of time since exposure
Week 2 - Cohort and C-C Studies24
Classifying Person-Time, cont.
How do you classify person-time contributed by exposed subjects before the minimum induction time has elapsed or after the maximum induction time has passed?
Example: – Exposure = Rotavirus vaccine– Outcome = Intussusception– Assume induction period ranges from 1-7 days
Exposure Disease Initiation
Induction periodWeek 2 - Cohort and C-C Studies25
Classifying Person-Time, cont.
Consider the time unexposed– BUT if the assumed induction time is incorrect, may
misclassify exposed time as unexposed = underestimate exposure effects
Omit person-time of exposed subjects when they are not at risk for the exposure effects
– Must be a large number of unexposed cases
Model exposure effects as depending on time since exposure
Week 2 - Cohort and C-C Studies26
Classifying Exposure
Exposure may change over time– Measure exposure constantly and classify each unit of
person-time A given individual can contribute person-time to one or more
exposure category in the same study
– Assume one measure of exposure history is the only aspect of exposure associated with current risk
Current, average, cumulative, etc.
Week 2 - Cohort and C-C Studies27
BASELINE QUESTIONNAIRE
Have you smoked 20 packs of cigarettes or more in your lifetime?
What specific brand and type?
If quit, how long ago?
At each age from <15 to 60+, what was the average number of cigarettes you smoked per day?
FOLLOW-UP QUESTIONNAIRES
Do you currently smoke cigarettes?
If so, how many per day?
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Different exposure metric = different assumptions
Classifying Exposure, cont.
Week 2 - Cohort and C-C Studies
Smoking–Current v. Not
•Assume former = never–Never v. Former v. Current
•Assume intensity & duration are not important–Pack-years
•Assume ½ pack for 10 y = 1 pack for 5 y = 5 packs for 1 y
29
Classifying Exposure, cont.
Pack-years is a composite of duration and intensity of smoking
If the biologic effects of these differ, a study examining pack-years would not detect these differences, and could result in a misleading dose-response pattern
Ideally, present results for pack-years and individual components of the primary exposure metric (e.g. smoking intensity and duration)
Week 2 - Cohort and C-C Studies30
Timing of Outcome Events
Events and the person-time being accumulated at the moment of the event are assigned to the same category of exposure
Must clearly define the outcome event, including a protocol for determining the timing of the event
Goal is to detect events at onset, however this may not be possible
– Date of diagnosis for cancer– Hospitalization for end-stage renal disease
Week 2 - Cohort and C-C Studies31
Immortal Person-Time
Entry criteria in a cohort may depend on survival– Study of pre-term birth and mortality in adulthood –
Individuals had to survive at least 1 year.
– Study of occupationally exposed workers – Workers had to be employed for at least 1 year.
First year of life = immortal person-time During this time, no one is at risk to become an
event in the study Exclude immortal person-time from the
denominator of incidence rates
Week 2 - Cohort and C-C Studies32
Lag exposure to account for induction time between exposure and disease initiation
– i.e. using Sufficient-component-cause model: time that it takes for the causal mechanism to be completed by the action of the complementary component causes
When lag period is not clear, need to hypothesize various induction times and reanalyze the data under each separate hypothesis. Also, can estimate the most appropriate time in the study by various statistical methods.
Lag Period (Induction Time)
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1. Background stratified Poisson regression analysis of cohort data. Richardson DB, Langholz B. Radiat Environ Biophys. 2012 Mar;51(1):15-22. 2.
2. Lagging exposure information in cumulative exposure-response analyses. Richardson DB, Cole SR, Chu H, Langholz B. Am J Epidemiol. 2011 Dec 15;174(12):1416-22.
3. Hierarchical latency models for dose-time-response associations. Richardson DB, MacLehose RF, Langholz B, Cole SR. Am J Epidemiol. 2011 Mar 15;173(6):695-702.
Recommended References
Week 2 - Cohort and C-C Studies34
Retrospective: both exposure and disease have occurred at start of study
Exposure------------------------Disease
*Study starts
Timing of cohort studies
Week 2 - Cohort and C-C Studies35
Prospective: exposure has (probably) occurred, disease has not occurred
Exposure----------------------Disease *Study starts
Ambi-directional: elements of both
Timing of cohort studies
Week 2 - Cohort and C-C Studies36
How do you choose between a retrospective and a prospective design?
Retrospective:
• Cheaper, faster• Efficient with diseases with long latent period• Exposure data may be inadequate
Timing of cohort studies
Week 2 - Cohort and C-C Studies37
How do you choose between a retrospective vs. prospective design?
Prospective:
• More expensive, time consuming• Not efficient for diseases with long latent
periods • Better exposure and confounder data• Less vulnerable to bias
Timing of cohort studies
Week 2 - Cohort and C-C Studies38
Selection of exposed population
Choice depends upon hypothesis under study and feasibility considerations
Issues in design of cohort studies
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Examples of exposed populations:
• Occupational groups• Groups undergoing particular medical treatment• Groups with unusual dietary or life style factors• Professional groups (nurses, doctors)• Students or alumni of colleges• Geographically defined areas (e.g.
Framingham)
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies40
For rare exposures, you need to assemble special cohorts (occupational groups, groups with unusual diets etc.)
Example of special cohort study• Rubber workers in Akron, Ohio• Exposure: industrial solvent• Outcomes: cancer
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies41
If exposure is common, you may want to use a general cohort that will facilitate accurate and complete ascertainment of data (Doctors, nurses, well-defined communities)
Issues in design of cohort studies
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• Framingham Study• Exposures: smoking, hypertension, family
history• Outcomes: heart disease, stroke, gout, etc.
Example of general cohort study
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Selection of comparison (unexposed) group
Principle: You want the comparison (unexposed) group to be as similar as possible to the exposed group with respect to all other factors except the exposure. If the exposure has no effect on disease occurrence, then the rate of disease in the exposed and comparison groups will be the same.
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies44
Selection of comparison (unexposed) group (cont’d)
Counterfactual ideal: The ideal comparison group consists of exactly the same individuals in the exposed group had they not been exposed. Since it is impossible for the same person to be exposed and unexposed simultaneously, epidemiologists much select different sets of people who are as similar as possible.
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies45
Three possible sources of comparison group
1. Internal comparison: unexposed members of same cohort
• Ex: Framingham study
Issues in design of cohort studies
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Three possible sources of comparison group
2. Comparison cohort: a cohort who is not exposed from another similar population
• Ex: Asbestos textile vs. cotton textile workers
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies47
3. General population data: Use pre-existing data from the general population as the basis for comparison. General population is commonly used in occupational studies. Usually find healthy worker effect
Ex. A study of asbestos and lung cancer with U.S. male population as the comparison group
Issues in design of cohort studies
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Which of the three comparison groups is best?
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Sources of exposure information:
* Pre-existing records - inexpensive, data recorded before disease occurrence but level of detail may be inadequate. Also, records may be missing, usually don't contain information on confounders
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies50
Sources of exposure information:
Questionnaires, interviews: good for information not routinely recorded but have potential for recall bias
Direct physical exams, tests, environmental monitoring may be needed to ascertain certain exposures.
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies51
Sources of outcome information:
Death certificates Physician, hospital, health plan records Questionnaires (verify by records) Medical exams
Issues in design of cohort studies
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Goal is to obtain complete follow-up information on all subjects regardless of exposure status. You can use blinding (like an experimental study) to ensure that there is comparable ascertainment of the outcome in both groups.
Various indices describing study quality: tracing, recruitment, retention and loss to follow-up rates.
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies53
Approaches to follow-up
In any cohort study, the ascertainment of outcome data involves tracing or following all subjects from exposure into the future.
Issues in design of cohort studies
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Approaches to follow-up:
Resources utilized to conduct follow-up: town lists, Polk directories, telephone books; birth, death, marriage records; driver's license lists, physician and hospital records; relatives, friends.
This is a time consuming process but high losses to
follow-up raise doubts about validity of study.
Issues in design of cohort studies
Week 2 - Cohort and C-C Studies55
Efficient for rare exposures, diseases with long induction and latent period
Can evaluate multiple effects of an exposure
If prospective, good information on exposures, less vulnerable to bias, and clear temporal relationship between exposure and disease
Strengths of Cohort Studies
Week 2 - Cohort and C-C Studies56
Inefficient for rare outcomes If retrospective, poor information on exposure
and other key variables, more vulnerable to bias
If prospective, expensive and time consuming, inefficient for diseases with long induction and latent period
Keep these strengths and weaknesses in mind for comparison with case-control studies
Weaknesses of Cohort Studies
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Case-Control Studies
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Case-Control Studies
Imagine a population in which a cohort study could be conducted
– Identify cases as you would in the cohort study– Sample from the study base (person-time) to determine
exposure distribution in the population that gave rise to the cases = Controls
– Controls must be sampled independent of exposure!
More efficient version of cohort study Sampling creates new opportunities for bias
Week 2 - Cohort and C-C Studies59
This disparaging term was given to case-control studies because their logic seemed backwards (trohoc is ?? spelled backwards) and they seemed more prone to bias than other designs.
No basis for this derogation. Case-control studies are a logical extension of
cohort studies and an efficient way to learn about associations.
“TROHOC” STUDIES
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A method of sampling a population in which cases
of disease are identified and enrolled, and a sample
of the population that produced the cases is
identified and enrolled. Exposures are determined
for individuals in each group.
General Definition of a Case-Control Study
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Where do you get information on the numerators?
Where do you get the information for the denominators?
Case-Control Studies as Approximation of Cohort Studies
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Where do you get information on the numerators? Cases = numerators of the rates of disease being compared you would have measured in exposed and unexposed groups in the corresponding cohort study
Where do you get the information for the denominators? If this were a cohort study, you would have the total population (if you were calculating cumulative incidence) or total person-years (if you were calculating incidence rates) for both the exposed and non exposed groups, which would provide the denominators for the compared rates. Controls = relative size of the exposed and unexposed person-time in the study base ≈ person-time denominators you would have measured in the corresponding cohort study
Case-Control Studies as Approximation of Cohort Studies
Week 2 - Cohort and C-C Studies63
A case-control study can be considered a more efficient form of a cohort study.
Cases are the same as those that would be included in a cohort study.
Controls provide a fast and inexpensive means of obtaining the exposure experience in the population that gave rise to the cases.
Case-Control Studies as Approximation of Cohort Studies, cont.
Week 2 - Cohort and C-C Studies64
Cases are the same people that would be cases in the underlying cohort study
– Can randomly sample cases if sampling is independent of exposure
Controls are a random, or conditionally random within strata, sample of study base
Exposure distribution in the controls is the same as in the population that gave rise to the cases, conditional on matching factors
Definitions of Cases and Controls
Week 2 - Cohort and C-C Studies65
Selection of Controls
Controls should be selected from the same population – the source population – that gave rise to the cases.
Controls should be selected independently of exposure, within strata of factors that will be used for stratification in the analysis.
Persons are eligible to be selected as a control as long as they are at risk for disease a person can be both a control and a case in the same study!
Week 2 - Cohort and C-C Studies66
Sources of Controls
Primary study base– Base population known
Study of Kaiser Permanente members Study conducted within existing cohort, “Nested case-control”
Secondary study base– Identify cases first, base population not known
Hospital-based case-control study
– Must identify person-time contributed by persons who would have become a case in your study had they developed the disease
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Advantages of general population controls
Because of selection process, investigator is usually assured that they come from the same base population as the cases.
Disadvantages of general population controls
Time consuming, expensive, hard to contact and get cooperation; may remember exposures differently than cases
Selecting Controls
Week 2 - Cohort and C-C Studies68
Neighborhood Controls
Sample residences May individually match cases to one or more
controls residing in the same neighborhood If neighborhood is associated with exposure,
must control for matching in the analysis Neighbors may not be the source population of
the cases– Cases at a VA hospital
Week 2 - Cohort and C-C Studies69
Friend/Family Controls
Being named as a friend control may be related to exposure
– Reclusive people are less likely to be named
Investigator dependent on cases for identifying controls
Friend groups often overlap, so persons with more friends are more likely to be selected as a control
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Random Digit Dialing
Case eligibility should include residence in a house with a telephone
Probability of calling a number ≠ probability of contacting an eligible control
– Households vary in the number of people, amount of time a person is at home, and the number of operating phones
Method requires a great deal of time and labor
Week 2 - Cohort and C-C Studies71
Random Digit Dialing, cont.
Answering machines, voicemail, and caller ID reduce response rates
Cell phones reduce validity of assuming source population can be randomly sampled using this method
– Recent CDC survey showed 2% increase in binge drinking compared to 2009 data – more cell phone numbers included, and average age of respondents decreased
May not be able to distinguish business and residential numbers - difficult to estimate proportion of non-responders
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Hospital-Based Controls
If not randomly selecting controls, must be cautious that control selection is independent of exposure
May not represent exposure distribution in source population if exposure is associated with hospitalization, other diseases, or both
– Example: Hospital-based study examining smoking and pancreatic cancer where controls are selected from persons admitted to the hospital for other conditions.
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Hospital-Based Controls, cont.
Limit diagnoses for controls to conditions with no association with the exposure
– May exclude most potential controls– Exclusion criteria only applies to the cause of the current
hospitalization
Reasonable to exclude categories of potential controls on the suspicion that a given category might be related to exposure
Imprudent to use only a single diagnostic category as a source of controls
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Exposure Disease Hospitalization
Hospital-Based Controls, cont.
Bias will occur if the exposure directly affects risk of being hospitalized, even if exposure is unrelated to the study disease or control diseases
Berkson’s Bias
Week 2 - Cohort and C-C Studies75
Advantages of hospital controls Same selection factors that led cases to hospital led controls to
hospital
Easily identifiable and accessible (so less expensive than population-based controls)
Accuracy of exposure recall comparable to that of cases since controls are also sick
More willing to participate than population-based controls
Selecting Controls
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Disadvantages of hospital controls
Since hospital based controls are ill, they may not accurately represent the exposure history in the population that produced the cases
Hospital catchment areas may be different for different diseases
Selecting Controls
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Deceased Controls
Not members of the source population for the cases
If exposure is associated with mortality, dead controls will misrepresent exposure distribution in source population
Even if cases are dead, generally better to choose living controls
Do not need a proxy interview for living controls of dead cases
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Comparability of Information
Comparability of information is often used to guide control selection and data collection
BUT– Non-differential exposure measurement error does not
guarantee that bias will be toward the null– Efforts to ensure equal accuracy of exposure data tend to
produce equal accuracy of data on other variables– Overall bias due to non-differential error in confounders and
effect modifiers can be larger than error produced by unequal accuracy of exposure data from cases and controls
Week 2 - Cohort and C-C Studies79
Measures of Association
IRR
Tx
Tx
Tfx
Tfx
TTyx
TTyx
yx
yxOR
00
11
00
11
0000
1111
00
11
Person-time Data
Exposed Unexposed
Cases x1 x0
Person-time T1 T0
Case-control Data
Exposed Unexposed
Cases x1 x0
Controls y1 y0
• Can also estimate the risk ratio or incidence odds ratio from case-control studies
• The measure of association estimated by the OR depends on the control sampling scheme
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Measures of Association
IRR
Tx
Tx
Tfx
Tfx
yx
yxOR
00
11
00
11
00
11
• Controls must be sampled independent of exposure: f1 = f0
• Generally, control sampling rate is not known, so cannot calculate incidence rates in exposed and unexposed
• Generally, rare disease assumption is NOT needed• As with cohort studies, the incidence odds ratio and rate
ratio are only good approximations of the risk ratio if the incidence proportion is less than 0.1
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Control Sampling Schemes
Control Sampling Method Description Measure of effect estimated by the OR
Case-cohort Persons at risk of disease at baseline
Risk ratio*Rate ratio
Density sampling Proportional to person-time accumulated by persons at risk of disease during follow-up
Rate Ratio
Cumulative case-control Persons at risk of disease who are non-cases at the end of follow-up
Incidence Odds Ratio Risk Ratio*
* Only need rare disease assumption when estimating the risk ratio from the odds ratio.
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Full Cohort Analysis
X
X
X
X
X
Time83
Control Sampling Schemes
Draw the sampling schemes on the open and closed cohort diagrams (X = case):
– Density Sampling– Incidence Density Sampling (“Risk Set Sampling”)– Case-Cohort Sampling– Cumulative Case Sampling
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Density Sampling
X
X
X
X
X
Time85
Density Sampling
X
X
X
X
X
Time86
Density Sampling
Sample controls at a steady rate per unit time over period in which cases are sampled
Probability of being selected as a control is proportional to amount of time person spends at risk of disease in source population
Individual may be selected as a control while they are at risk for disease, and subsequently become a case
Incidence density sampling or “risk set sampling” is a form of density sampling in which you match cases and controls on time
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Risk Set Sampling
X
X
X
X
X
Time88
Risk Set Sampling
X
X
X
X
X
Time89
Case-Cohort Sampling
X
X
X
X
X
Time90
Case-Cohort Sampling
X
X
X
X
X
Time91
Closed Cohort Analysis
X
X
X
X
X
Time92
Cumulative Sampling
X
X
X
X
X
Time93
Cumulative Sampling
X
X
X
X
X
Time94
Exposure Classification
Same principles as discussed for cohort studies Cases’ exposure should be classified as of the
time of diagnosis or disease onset, accounting for induction time hypotheses
Controls should be classified according to their exposure status at the time of selection, accounting for induction time hypotheses
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Timing of Exposure Classification
Selection time does not necessarily refer to the time at which a control is first identified
– For hospital-based controls, selection time may be date of diagnosis for the disease that resulted in the current hospitalization
– Date of interview is often used if there is not an event analogous to the cases’ date of diagnosis
Interviewers should be blinded to case-control status whenever possible
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Case-cohort Nested case-control Case-control studies without controls
– Traditional case series– Case-crossover – Case-specular
Variations in case-control study designs
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1. Sample the population at risk at the start of the observation period
*-------------------------------------------------------------------------*Start FU End FU ^^
2. Sample population at risk as cases develop*-------------------------------------------------------------------------*Start FU End FU ^ ^ ^ ^^^ ^
3. Sample survivors at the end of the observation period*------------------------------------------------------------------------*Start FU End FU ^^
Sampling a cohort population for controls: nested case-control study
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When exposure data are expensive or difficult to obtain- Ex: Pesticide and breast cancer study
When disease has long induction and latent period- Ex: Cancer, cardiovascular disease
When the disease is rare
– Ex: Studying risk factors for birth defects
When little is known about the disease– Ex. Early studies of AIDS
When underlying population is dynamic– Ex: Studying breast cancer on Cape Cod
When is it desirable to conduct a case-control study?
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Summary
Causal models inform decisions made in the design phase of a study
Every decision made by the investigator comes with its own set of assumptions
Cohort study = Analogous to RCT, but investigator does not assign exposure
Case-control study = Analogous to cohort study, but with more efficient sampling
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Comparisons between Case-control and Cohort study design
Characteristics Case-control Cohort studySelect subjects based on Disease status Exposure Status
Exposure good for common exposures Good for rare exposures
Cost-effectiveness Cheaper and less time consuming
Expensive and time consuming
Disease Frequency Good for rare diseases Good for common diseases
Establish temporal order Temporality generally not clear Temporality generally clear
Incidence calculation Can not calculate incidence/risk/rate
Can calculate incidence risk or rate depending on study design
Study more than one outcome
No Yes
Examine >1 exposure Yes Generally no
Inherent Study Selection problem
Difficult to ascertain appropriate control group
Not applicable since start with a source population
Subject to biases Susceptible to more biasesParticularly recall bias
Less subject to biases-except to loss to follow-up (Loss of subjects due to migration, lack of participation, withdrawal & death)
Directionality Prospective/retrospective Prospective/retrospective
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In theory, it's possible to use each design to test a hypothesis
Example: Suppose you want to study the relationship between dietary Vitamin A and lung cancer….
Which study design to choose?
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Subjects are chosen on the basis of exposure status and followed to assess the occurrence of disease
High Vitamin A consumption ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑> lung cancer
or not
Low Vitamin A Consumption ‑‑‑‑‑‑‑‑‑‑‑‑‑‑> lung cancer or not
What are the advantages and disadvantages of this option?
Cohort Study Option
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Special type of cohort study in which investigator assigns the exposure to individuals, preferably at random
Investigator assigns exposure to:
High Vit A consumption ‑‑‑‑‑‑‑‑‑‑‑‑‑-‑‑> lung cancer or not
Low Vit A consumption ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑> lung cancer or not
What are the advantages and disadvantages of this option?
Experimental Study Option
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Cases with the disease and controls who generally do not have the disease are chosen and past exposure to a factor is determined
Prior Vitamin A consumption <‑‑‑‑------- lung cancer cases Prior Vitamin A consumption <‑‑‑‑‑‑‑‑‑‑ controls
What are the advantages and disadvantages of this option?
Case‑Control Study Option
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State of knowledge
Frequency of exposure and disease
Time, cost and other feasibility considerations
Each study design has unique and complementary advantages and disadvantages
In practice, choice of study design depends on:
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1. H. Checkoway H, N. Pearce N, D. Kriebel. Selecting appropriate study designs to address specific research questions in occupational epidemiology. Occup Environ Med 2007 Sep;64(9):633-8.
2. J. H. Fowke. Issues in the design of molecular and genetic epidemiologic studies. J Prev Med Public Health 2009 Nov;42(6):343-8.
Recommended References
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Efficient for rare diseases and diseases with long induction and latent period.
Can evaluate many risk factors for the same disease so good for diseases about which little is known
Strengths of case-control studies
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Inefficient for rare exposures Vulnerable to bias because of retrospective
nature of study May have poor information on exposure
because retrospective Difficult to infer temporal relationship between
exposure and disease
How do these strengths and weaknesses compare to cohort studies?
Weaknesses of case-control studies
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Field methods
o Operations Manuals
o Staff training and re-training, certification
o Quality control measures
o Assessment of progress
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